Recommended Modelling Technique for Influencer Marketing Scenario
It depends very much on the structure of the data.

I would think about feature extraction first, which could be certain words occurring in the bio, and a class of user name ('real' name, numerical id, etc). Once you have a set of features for each data item, turn them into a list of feature vectors.

Then run them through a number of machine learning algorithms. This is where the shape of the data matters, as some algorithms will work better than others. I would try eg decision trees (ID3), which are very efficient once trained (but they don't give you a confidence interval). But any other ML algorithm might work. They will all have trade-offs with speed of training, memory requirements, and speed of classification; some will give you a class-label probability, others will just give you one label.

The best way would be to use a sample, and identify which algorithm works well and fits your specific requirements. Then use that for the full data set.

Alternatively you could just use, for example, the Stanford ML classifier. That will give you a confidence interval, and will probably work reasonably well.